Extending the lead time of precipitation nowcasts is vital to improvements in heavy rainfall warning, flood mitigation, and water resource management. Because the TREC vector （tracking radar echo by correlation） rep...Extending the lead time of precipitation nowcasts is vital to improvements in heavy rainfall warning, flood mitigation, and water resource management. Because the TREC vector （tracking radar echo by correlation） represents only the instantaneous trend of precipitation echo motion, the approach using derived echo motion vectors to extrapolate radar reflectivity as a rainfall forecast is not satisfactory if the lead time is beyond 30 minutes. For longer lead times, the effect of ambient winds on echo movement should be considered. In this paper, an extrapolation algorithm that extends forecast lead times up to 3 hours was developed to blend TREC vectors with model-predicted winds. The TREC vectors were derived from radar reflectivity patterns in 3 km height CAPPI （constant altitude plan position indicator） mosaics through a cross-correlation technique. The background steering winds were provided by predictions of the rapid update assimilation model CHAF （cycle of hourly assimilation and forecast）. A similarity index was designed to determine the vertical level at which model winds were applied in the extrapolation process, which occurs via a comparison between model winds and radar vectors. Based on a summer rainfall case study, it is found that the new algorithm provides a better forecast.展开更多
机载雷达具有速度快、视野广的特点,适用于战场运动目标的跟踪识别。而目前国内外针对机载低分辨雷达下微动地面目标识别的研究尚属空白。文中建立了机载平台下战场目标的雷达回波散射点模型,分析了单兵、轮式车、履带车等典型目标的微...机载雷达具有速度快、视野广的特点,适用于战场运动目标的跟踪识别。而目前国内外针对机载低分辨雷达下微动地面目标识别的研究尚属空白。文中建立了机载平台下战场目标的雷达回波散射点模型,分析了单兵、轮式车、履带车等典型目标的微动特性,根据行进单兵微多普勒的周期性特征实现了单兵与机动车的识别;进而通过提取回波信号特征谱和支持向量机的方法实现轮式车与履带车的分类,在20 d B信噪比下识别率在87.5%以上。分类方法具有稳健性和有效性。展开更多
基金This study was provided by Natural Science Foundation of Guangdong Province under Grant No. 5001121the China Meteorological Administration under Grant Nos. CMATG2005Y05 and CMATG2008Z10the Guangdong Meteorological Bureau under Grant Nos. 2007A2 and GRMC2007Z03
文摘Extending the lead time of precipitation nowcasts is vital to improvements in heavy rainfall warning, flood mitigation, and water resource management. Because the TREC vector （tracking radar echo by correlation） represents only the instantaneous trend of precipitation echo motion, the approach using derived echo motion vectors to extrapolate radar reflectivity as a rainfall forecast is not satisfactory if the lead time is beyond 30 minutes. For longer lead times, the effect of ambient winds on echo movement should be considered. In this paper, an extrapolation algorithm that extends forecast lead times up to 3 hours was developed to blend TREC vectors with model-predicted winds. The TREC vectors were derived from radar reflectivity patterns in 3 km height CAPPI （constant altitude plan position indicator） mosaics through a cross-correlation technique. The background steering winds were provided by predictions of the rapid update assimilation model CHAF （cycle of hourly assimilation and forecast）. A similarity index was designed to determine the vertical level at which model winds were applied in the extrapolation process, which occurs via a comparison between model winds and radar vectors. Based on a summer rainfall case study, it is found that the new algorithm provides a better forecast.
文摘机载雷达具有速度快、视野广的特点,适用于战场运动目标的跟踪识别。而目前国内外针对机载低分辨雷达下微动地面目标识别的研究尚属空白。文中建立了机载平台下战场目标的雷达回波散射点模型,分析了单兵、轮式车、履带车等典型目标的微动特性,根据行进单兵微多普勒的周期性特征实现了单兵与机动车的识别;进而通过提取回波信号特征谱和支持向量机的方法实现轮式车与履带车的分类,在20 d B信噪比下识别率在87.5%以上。分类方法具有稳健性和有效性。
